Hiring at $200K Annual Salary: Wall Street Advances into Prediction Markets

marsbitОпубліковано о 2026-01-15Востаннє оновлено о 2026-01-15

Анотація

Wall Street firms are aggressively entering the prediction markets, with trading giants like DRW, Susquehanna, and Tyr Capital building specialized teams. DRW is offering up to $200,000 in base salary to hire traders who can monitor and trade on platforms like Polymarket and Kalshi. Trading volume in these markets surged from under $100 million in early 2024 to over $8 billion by December 2025, attracting institutional interest. Unlike retail traders who often bet on single events, institutions focus on cross-platform arbitrage and structural opportunities. For example, hedge funds can use prediction markets to hedge investments with greater precision by pairing positions—such as buying "no recession" contracts on Polymarket while shorting overvalued bonds in credit markets. Market makers like Susquehanna, which has privileged access to lower fees and higher limits on platforms like Kalshi, are set to reduce arbitrage opportunities and improve liquidity. This professionalization may lead to more complex products, such as multi-event combos and conditional probability contracts. The entry of well-capitalized, technologically advanced institutions signals a maturation of prediction markets, mirroring the historical pattern of散户-driven innovation eventually dominated by professional players. While retail traders may find niches in long-tail events, the era of easy profits from informational edges is likely over.

Author: Niusike, Deep Tide TechFlow

It has finally arrived. The prediction markets, once built by political supporters, speculative retail investors, and airdrop hunters, are now welcoming a group of silent yet deadly new players.

According to a Thursday report by the Financial Times, several well-known trading firms, including DRW, Susquehanna, and Tyr Capital, are forming specialized prediction market trading teams.

DRW posted a job advertisement last week, offering a base annual salary of up to $200,000 for traders capable of "monitoring and trading active markets in real-time" on platforms like Polymarket and Kalshi.

Options trading giant Susquehanna is recruiting prediction market traders who can "detect incorrect fair value," identify "anomalous behavior" and "inefficiencies" in prediction markets, and is also building a dedicated sports trading team.

Crypto hedge fund Tyr Capital is continuously hiring prediction market traders who are "already running complex strategies."

Data supports this ambitious expansion.

Monthly trading volume surged from less than $100 million at the beginning of 2024 to over $8 billion by December 2025, with a record single-day trading volume of $701.7 million on January 12.

When the pool of funds becomes deep enough to accommodate the size of giants, Wall Street's entry becomes inevitable.

Arbitrage First

In prediction markets, institutions and retail investors are not playing the same game.

Retail investors often rely on fragmented information to predict single events, which is essentially gambling, while institutional players focus on cross-platform arbitrage and structural market opportunities.

In October 2025, Boaz Weinstein, founder of hedge fund Saba Capital Management, stated at a closed-door meeting that prediction markets allow portfolio managers to hedge investments with greater precision, particularly regarding the probability of specific events occurring.

Standing next to Polymarket CEO Shayne Coplan at the time, he said, "A few months ago, Polymarket showed a 50% probability of recession, while the credit market indicated a risk of about 2%. You can think of countless paired trades that were previously impossible."

According to Weinstein's view, a fund manager could buy the "no recession" contract on Polymarket. Because the market believed there was a 50% chance of recession, this contract was relatively cheap.

At the same time, in the credit market, one could short some bonds or credit products that would fall sharply in a recession. Because the credit market only assigned a 2% probability to a recession, these products were still priced high.

If a recession did occur, you would lose a small amount on Polymarket, but make a large profit in the credit market as those overvalued bonds plummet.

If no recession occurred, you would make money on Polymarket and might incur a small loss in the credit market, but overall still profit.

The emergence of prediction markets has provided traditional financial markets with a new "price discovery tool."

The Arrival of the Privileged Class

What tilts the scales even further is privilege at the regulatory level.

Susquehanna is the first market maker on Kalshi and has reached an event contract agreement with Robinhood.

Kalshi offers market makers numerous benefits: lower fees, special trading limits, and more convenient trading channels. The specific terms are not public.

The entry of market makers will quickly change this market.

Previously, prediction markets often suffered from insufficient liquidity, especially for niche events. When you wanted to buy or sell a large number of contracts, you might face wide spreads or simply no counterparty.

Professional institutions will quickly eliminate obvious pricing errors. For example, price differences for the same event on different platforms, or clearly unreasonable probability pricing, will be rapidly smoothed out.

This is not good news for retail investors. Previously, you might find that "Trump wins" was at a 60% probability on Polymarket and 55% on Kalshi, allowing for simple arbitrage. In the future, such opportunities will基本ally not exist.

With Wall Street's PhDs earning hundreds of thousands of dollars, future prediction contracts may also enter an era of specialization and diversification, not just单一 event prediction, such as:

1. Multi-event combination contracts, similar to parlays in sports betting

2. Time series contracts, predicting the probability of an event occurring within a specific time period

3. Conditional probability products, e.g., if A happens, what is the probability of B happening

......

Looking back at financial history, from foreign exchange to futures, to cryptocurrencies, the development of every emerging market follows a similar trajectory: ignited by retail investors, eventually taken over by institutions.

Prediction markets are repeating this process. Technological advantages, capital scale, and privileged access will ultimately determine who stays in this game of probability until the end.

For retail investors, although there may still be a glimmer of hope in long-cycle predictions or niche areas, they must face reality. When Wall Street's精密 machines start running at full speed, the狂欢 period of easy profits from information asymmetry may be gone forever.

Пов'язані питання

QWhat is the reported base salary that DRW is offering to traders for monitoring and trading on prediction market platforms?

A$200,000

QWhich specific prediction market platforms are mentioned in the article as being targeted by the new trading teams from firms like DRW?

APolymarket and Kalshi

QAccording to Boaz Weinstein, how can hedge fund managers use prediction markets to hedge their investments more precisely?

AThey can use prediction markets to hedge against the probability of specific events occurring, such as by creating trades that pair a position on a prediction market with an opposite position in a traditional market like credit.

QWhat advantage does the article state that market makers like Susquehanna have on platforms such as Kalshi?

AThey receive benefits such as lower fees, special trading limits, and more convenient trading channels, the specific terms of which are not publicly disclosed.

QWhat does the article suggest is the likely outcome for retail traders as large institutional players enter the prediction market space?

AThe era of easy profits from information asymmetry is likely over for retail traders, as institutions will quickly eliminate pricing errors and arbitrage opportunities, though some opportunity may remain in long-cycle predictions or niche areas.

Пов'язані матеріали

How to Automate Any Workflow with Claude Skills (Complete Tutorial)

This is a comprehensive guide to mastering Claude Skills, a feature for creating permanent, reusable instruction sets that automate specific workflows. Unlike simple saved prompts, Skills function like trained employees, delivering consistent, high-quality outputs by defining the entire task process, standards, error handling, and output format. The guide is structured in four phases: **Phase 1: Installation (5 minutes).** Skills are folders containing a `SKILL.md` file. The user is instructed to find a relevant Skill online, install it, test it on a real task, and compare its performance to one-off prompts. **Phase 2: Building Your First Custom Skill.** Start by rigorously defining the Skill's purpose, trigger phrases, and providing a concrete example of perfect output. The `SKILL.md` file has two parts: a YAML frontmatter with a specific name/description/triggers, and a detailed, step-by-step workflow written in natural language with examples and quality standards. **Phase 3: Testing & Optimization for Production.** Test the Skill in three scenarios: 1) a standard, common task; 2) edge cases with missing or conflicting data; and 3) a pressure test with maximum complexity. Any failure indicates a needed instruction. Implement a weekly optimization cycle to continuously refine the Skill based on real usage. **Phase 4: Building a Complete Skill Library.** The goal is to create a team of Skills for all repetitive tasks. Examples are given for industries like real estate, marketing, finance, consulting, and e-commerce. The user should list their tasks, prioritize them, and build one new Skill per week, maintaining a master document to track their library. The conclusion emphasizes the compounding time savings: ten Skills saving 30 minutes each per week reclaims over 260 hours (6.5 work weeks) per year, fundamentally transforming one's work system.

marsbit19 хв тому

How to Automate Any Workflow with Claude Skills (Complete Tutorial)

marsbit19 хв тому

Dialogue with Vitalik, Xiao Feng, Aya Miyaguchi, and Joseph Chalom: From the 'Subtraction Principle' to the Agent Economy

Conversation with Vitalik Buterin, Xiao Feng, Aya Miyaguchi, and Joseph Chalom: Highlights from the Ethereum Application Summit on key future directions. Vitalik Buterin discussed the concept of "Full Stack Open Source Security," extending security from the protocol to hardware layers like wallets and chips. He predicted AI will simplify blockchain interaction, enabling natural language commands for complex operations. He emphasized that Ethereum's future focus should be on security, decentralization, and trustless infrastructure—the areas where it holds its core competitive edge. The fusion of AI, Fully Homomorphic Encryption (FHE), and blockchain is seen as crucial for real-world applications requiring privacy, such as healthcare. Xiao Feng underscored the importance of simplifying technology for mass adoption. He drew parallels to the evolution from command lines to GUIs and apps, suggesting that AI-driven natural language interfaces will be key to bringing more users into Web3. He stressed that while performance is important, Ethereum must continue to uphold its foundational principles of decentralization and user sovereignty. Aya Miyaguchi, Chair of the Ethereum Foundation, explained the evolving role of the Foundation through the "Principle of Subtraction." As the ecosystem matures, the EF is stepping back from areas where the community can take the lead, acting as one of many "gardeners" rather than a central driver. She highlighted that real applications are built on Ethereum's core values: censorship resistance, open source, security, and privacy. The concept of "Local-first" initiatives, like the Ethereum Applications Guild (EAG), was also emphasized for leveraging regional strengths to create global impact. Joseph Chalom, CEO of SharpLink, positioned Ethereum as the future infrastructure for global capital markets, differentiating it from Bitcoin through its "productivity" via staking yields. He envisioned the rise of an "Agent Economy" by 2027, where AI agents, powered by Web3 wallets, will autonomously manage financial tasks like yield optimization and RWA investments. The summit concluded that with core infrastructure maturing, the application layer is now the key driver for Ethereum's next phase of growth and real-world adoption.

marsbit21 хв тому

Dialogue with Vitalik, Xiao Feng, Aya Miyaguchi, and Joseph Chalom: From the 'Subtraction Principle' to the Agent Economy

marsbit21 хв тому

Cerebras IPO: A $48.8 Billion Valuation—Is the 'Nvidia Challenger' a Bubble or a New King?

Cerebras Systems, positioning itself as an NVIDIA challenger, is going public with a $48.8 billion valuation despite several underlying paradoxes revealed in its S-1 filing. While 2025 revenue grew 76% to $510M and GAAP net income was $237.8M, this profitability relies heavily on a one-time, non-cash accounting gain. Adjusting for this, the company's non-GAAP net loss actually widened to $75.7M. Furthermore, customer concentration remains extreme: 86% of 2025 revenue came from two Abu Dhabi-based entities, MBZUAI (62%) and G42 (24%). Its landmark deal with OpenAI, valued at over $20 billion, creates a complex, nested relationship where OpenAI is simultaneously a major customer, lender, warrant holder, and strategic partner with exclusivity clauses. Cerebras's technical edge in latency-sensitive AI inference is real, with its wafer-scale chip outperforming competitors in benchmarks. However, this advantage is confined to a specific niche, not the broader AI training market dominated by NVIDIA's CUDA ecosystem. With a 95x price-to-sales ratio, the valuation demands flawless execution of the OpenAI contract and massive future revenue growth. Key long-term risks include intense competition from giants like NVIDIA and AMD, a dual-class share structure granting insiders near-total voting control, and ongoing geopolitical uncertainties regarding export controls. The IPO is a pivotal capital markets event for AI infrastructure. As an investment, it represents a high-risk, high-reward bet on the "inference-first" narrative and Cerebras's ability to dominate its specialized segment, underpinned by a valuation that highlights the current fervor in the sector.

marsbit59 хв тому

Cerebras IPO: A $48.8 Billion Valuation—Is the 'Nvidia Challenger' a Bubble or a New King?

marsbit59 хв тому

Торгівля

Спот
Ф'ючерси
活动图片